NDLI: Linear prediction analysis of speech with set-membership constraints: experimental results

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Linear prediction analysis of speech with set-membership constraints: experimental results

Content Provider	IEEE Xplore Digital Library
Author	Deller Jr., J.R.
Copyright Year	1990
Description	Author affiliation: Dept. of Electr. Eng., Michigan State Univ., East Lansing, MI, USA (Deller, J.R., Jr.)
Abstract	Set-membership (SM) identification refers to a class of techniques for estimating parameters of linear system or signal models under a priori information which constrains the solutions to certain sets. When data do not help refine these membership sets, the effort of updating the parameter estimates at those points can be avoided. An application of the SM method to the problem of identifying the linear prediction (LP) parameters of speech is discussed, emphasizing experimental findings of practical significance.<>
Starting Page	113
Ending Page	116
File Size	458072
Page Count	4
File Format	PDF
DOI	10.1109/MWSCAS.1989.101807
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1989-08-14
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Speech analysis Samarium Signal processing algorithms Parameter estimation Equations Least squares methods Recursive estimation Digital signal processing Laboratories State estimation
Content Type	Text
Resource Type	Article

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